FAQ
Dear gurus,
I've analyzed a (fake) data set ("data") using logistic regression (glm):

logreg1 <- glm(z ~ x1 + x2 + y, data=data, family=binomial("logit"),
na.action=na.pass)

Then, I created a data frame with 2 fixed levels (0 and 1) for each predictor:

attach(data)
x1<-c(0,1)
x2<-c(0,1)
y<-c(0,1)
newdata1<-data.frame(expand.grid(x1,x2,y))
names(newdata1)<-c("x1","x2","y")

Finally, I calculated model-predicted probabilities for each
combination of those fixed levels:

newdata1\$predicted <-predict(logreg1,newdata=newdata1, type="response")

I am pretty sure the results I get (see the table below) are actual
probabilities. But just in case - could someone please confirm that
these are probabilities rather than log odds or odds?
Thanks a lot!

x1 x2 y predicted
1 0 0 0 0.08700468
2 1 0 0 0.19262901
3 0 1 0 0.27108334
4 1 1 0 0.48216220
5 0 0 1 0.53686154
6 1 0 1 0.74373367
7 0 1 1 0.81896484
8 1 1 1 0.91887072
--
Dimitri Liakhovitski

Dimitri.Liakhovitski at ninah.com

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• at Feb 18, 2010 at 7:38 pm ⇧ On 18-Feb-10 18:58:57, Dimitri Liakhovitski wrote:
Dear gurus,
I've analyzed a (fake) data set ("data") using logistic regression
(glm):

logreg1 <- glm(z ~ x1 + x2 + y, data=data, family=binomial("logit"),
na.action=na.pass)

Then, I created a data frame with 2 fixed levels (0 and 1) for each
predictor:

attach(data)
x1<-c(0,1)
x2<-c(0,1)
y<-c(0,1)
newdata1<-data.frame(expand.grid(x1,x2,y))
names(newdata1)<-c("x1","x2","y")

Finally, I calculated model-predicted probabilities for each
combination of those fixed levels:

newdata1\$predicted <-predict(logreg1,newdata=newdata1, type="response")

I am pretty sure the results I get (see the table below) are actual
probabilities. But just in case - could someone please confirm that
these are probabilities rather than log odds or odds?
Thanks a lot!

x1 x2 y predicted
1 0 0 0 0.08700468
2 1 0 0 0.19262901
3 0 1 0 0.27108334
4 1 1 0 0.48216220
5 0 0 1 0.53686154
6 1 0 1 0.74373367
7 0 1 1 0.81896484
8 1 1 1 0.91887072
--
Dimitri Liakhovitski
Yes, they are predicted probabilities of response Z=1.
You specified this by setting 'type="response"'.

See ?predict.glm (the method for 'predict' which is used for GLMs).

Ted.

--------------------------------------------------------------------
E-Mail: (Ted Harding) <ted.harding@manchester.ac.uk>
Fax-to-email: +44 (0)870 094 0861
Date: 18-Feb-10 Time: 19:38:54
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